DOCSLIB.ORG

A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges sensors Review A Survey of Autonomous Vehicles: Enabling Communication Technologies and Challenges M. Nadeem Ahangar 1, Qasim Z. Ahmed 1,*, Fahd A. Khan 2 and Maryam Hafeez 1 1 School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK; [email protected] (M.N.A.); [email protected] (M.H.) 2 School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad 44000, Pakistan; [email protected] * Correspondence: [email protected] Abstract: The Department of Transport in the United Kingdom recorded 25,080 motor vehicle fatali- ties in 2019. This situation stresses the need for an intelligent transport system (ITS) that improves road safety and security by avoiding human errors with the use of autonomous vehicles (AVs). There- fore, this survey discusses the current development of two main components of an ITS: (1) gathering of AVs surrounding data using sensors; and (2) enabling vehicular communication technologies. First, the paper discusses various sensors and their role in AVs. Then, various communication tech- nologies for AVs to facilitate vehicle to everything (V2X) communication are discussed. Based on the transmission range, these technologies are grouped into three main categories: long-range, medium- range and short-range. The short-range group presents the development of Bluetooth, ZigBee and ultra-wide band communication for AVs. The medium-range examines the properties of dedicated short-range communications (DSRC). Finally, the long-range group presents the cellular-vehicle to everything (C-V2X) and 5G-new radio (5G-NR). An important characteristic which differentiates each category and its suitable application is latency. This research presents a comprehensive study of AV technologies and identifies the main advantages, disadvantages, and challenges. Citation: Ahangar, M.N.; Ahmed, Q.Z.; Khan, F.A.; Hafeez, M. A Survey Keywords: autonomous vehicles; Bluetooth; dedicated short-range communications; intelligent of Autonomous Vehicles: Enabling transport system; V2I; V2V; V2X; VANET; vehicular communications; ultra-wide band; ZigBee Communication Technologies and Challenges. Sensors 2021, 21, 706. https://doi.org/10.3390/s21030706 1. Introduction Academic Editor: Fatih Kurugollu and Francisco J. Martinez Technology facilitates humans, improves productivity and leads to a better quality Received: 18 December 2020 of life. Technological developments and automation in vehicular networks will lead to Accepted: 18 January 2021 better road safety and lower congestion in present urban areas where the traditional Published: 21 January 2021 transport system is becoming increasingly disorganised and inefficient [1]. Therefore, the development of the intelligent transport systems (ITS) concept has been proposed, with the Publisher’s Note: MDPI stays neu- aim and focus on improving traffic safety and providing different services to its users [2,3]. tral with regard to jurisdictional clai- There has been considerable research in ITS resulting in significant contributions (see [4] ms in published maps and institutio- and references therein). Figure1 shows the three main applications of the ITS system: (1) nal affiliations. Applications for transport efficiency; (2) Safety-critical applications; and (3) Infotainment applications. The main task of the transport efficiency application includes the calculation of the optimal speed and the route to navigate the vehicle to the destination by taking into account the traffic information [5]. Safety-critical applications deal with the response to Copyright: © 2021 by the authors. Li- censee MDPI, Basel, Switzerland. emerging vehicles and intersection collision avoidance [5]. Infotainment applications deal This article is an open access article with cooperative local services such as the location of petrol stations, hotels, etc. [5]. distributed under the terms and con- One of the most significant contributions towards the ITS has been the development ditions of the Creative Commons At- of autonomous vehicles (AVs). These vehicles perceive the environment through sensing tribution (CC BY) license (https:// using various sensors, and then this information is utilised to drive without the need for creativecommons.org/licenses/by/ any human intervention [6]. In Figure2, the technical evolution of AVs is illustrated in 4.0/). detail. The modern cruise control system was developed in 1948 and since then self-driving Sensors 2021, 21, 706. https://doi.org/10.3390/s21030706 https://www.mdpi.com/journal/sensors Sensors 2021, 21, 706 2 of 33 cars have been gradually developing different features [7,8]. Significant developments were made in the early 2000s when the lane departure warning system (LDWS), adaptive cruise control (ACC), self-parking assistance (SPA), auto-pilot and traffic sign recognition (TSR) were developed for AVs [9–11]. It is planned that by 2022 we will have intelligent speed adaptation systems and by 2030 fully automated AVs will be available with no driver backup required. This advancement will further lead to the next emerging and evolutionary stage of the Internet of vehicles (IoV). In IoV networks, besides human as users of the Internet, physical sensors, machine-type devices and vehicles will be the users of the IoV ecosystem. Figure 1. Different applications for intelligent transport system (ITS). Figure 2. Technical evolution in autonomous cars. The Society of Automotive Engineers (SAE) classified the vehicles into six different levels of automation. The same classification is also adopted by other organisations such as the International Organisation of Motor Vehicle Manufacturer (OICA) and the German Federal Highway Research Institute (BASt). The US National Highway Traffic Safety Administration (NHTSA) initially had a different classification, as compared in Table1[12]. Since then, NHTSA has also adopted SAE’s six levels of automation in the Federal Automated Vehicle Policy. Levels 0–2 can be broadly categorised as driver assisted, while Levels 3 and 4 can be termed as semi-automatic and Level 5 is fully autonomous. The detailed features of each level are described below: • Level 0 is not automated, and all the tasks are performed by the driver. • Level 1 provides driver assistance with some functions such as ACC, TSR, etc., but the driver controls the accelerator and the brakes while monitoring the surroundings. • Level 2 provides partial driving assistance, and the vehicle can perform the steer- ing and acceleration functions. However, the driver is responsible for many safety- critical actions. • Level 3 provides conditional driving automation where the vehicle performs the entire monitoring of the surroundings. The driver is no longer responsible for safety- critical issues. Sensors 2021, 21, 706 3 of 33 • Level 4 provides high driving automation, and the driver holds control only if the automated situation turns unsafe. Steering, braking, acceleration and surrounding check are performed by the vehicle. • Level 5 represents complete automation where there is no need for human intervention and the driver is a passenger. Figure3 summarises the above discussed features and functions achieved at each level according to the SAE J3016 standard [12]. Table 1. Comparison between different automation levels. Organisation Level 0 Level 1 Level 2 Level 3 Level 4 Level 5 BASt, SAE, Driver Driver Partial Conditional High Full OICA Only Assisted Automation Automation Automation Automation NHSTA No Function Combined Limited Fully Specific Function Self-Driving Self-Driving Figure 3. Different levels of automation. Autonomous vehicles have several advantages including improved safety and lower road congestion resulting in lower fuel/energy consumption [4,6]. Besides these advan- tages, there are some issues which need to be resolved for AVs such as who bears the legal responsibilities of the AVs, what will the course of action be if the AV controller is hacked, etc. A summary of the main pros and cons of AVs are listed in Table2. Overall, it can be claimed that, if the drawbacks are resolved or minimised, then autonomous cars will be a considerable technological development in coming years as they will facilitate people’s lives and increase road safety [10,13]. This paper aims to review the advancement of autonomous cars focusing on the various sensors deployed in them along with the different communication technologies employed. Therefore, the objectives of this survey are as follows: • To identify and describe the different type of sensors used in AVs. • To classify communication technologies based on their transmission range and identify their main advantages and disadvantages. This implies: 1. Discussing short-range technologies such as Bluetooth, ZigBee and ultra-wide band (UWB) 2. Assessing medium-range technologies such as dedicated short-range communi- cation (DSRC) and Wireless Fidelity (Wi-Fi) 3. Analysing long-range technologies such as Cellular Vehicle To Everything (C- V2X) and Fifth Generation-New Radio (5G-NR) technology The survey is organised as follows. Section2 presents the literature review. Section3 discusses the system architecture for the AVs with emphasis on the various types of sensors. Section4 analyses the Vehicular Ad-hoc Networks (VANETs) and the Vehicle- to-Everything (V2X) technologies. Section5 discusses the classification of the different wireless technologies based on the transmission range and their applications and challenges Sensors 2021, 21, 706 4 of 33 in AVs and ITS. Finally,
Load more

Recommended publications
  • Handheld Computing Terminal Industrializing Mobile Gateway for the Internet of Things
    Handheld Computing Terminal Industrializing Mobile Gateway for the Internet of Things Retail Inventory Logistics Management Internet of Vehicles Electric Utility Inspection www.AMobile-solutions.com About AMobile Mobile Gateway for IIoT Dedicated IIoT, AMobile develops mobile devices and gateways for data collectivity, wireless communications, local computing and processing, and connectivity between the fields and cloud. In addition, AMobile's unified management platform-Node-Watch monitors and manages not only mobile devices but also IoT equipment in real-time to realize industrial IoT applications. Manufacturing • IPC mobile • Mobility computing technology Retail Inspection (IP-6X, Military • Premier member grade, Wide- - early access Blockchain temperature) Healthcare Logistics • Manufacturing resource pool Big Data & AI • Logistics • Global customer support Handheld Mobile Computing Data Collector Smart Meter Mobile Inspection Device with Keyboard Assistant Mobile Computing IoT Terminal Device Ultra-rugged Intelligent Barcode Reader Vehicle Mount Handheld Device Handheld Device Tablet Mobile Gateway AMobile Intelligent established in 2013, a joint venture by Arbor Technology, MediaTek, and Wistron, is Pressure Image an expert in industrial mobile computers and solutions for industrial applications including warehousing, Temperature Velocity Gyroscope logistics, manufacturing, and retail. Leveraging group resources of manufacturing and services from Wistron, IPC know-how and distribution channels from Arbor, mobility technology and
    [Show full text]
  • A Survey of Autonomous Driving: Common Practices and Emerging Technologies
    Accepted March 22, 2020 Digital Object Identifier 10.1109/ACCESS.2020.2983149 A Survey of Autonomous Driving: Common Practices and Emerging Technologies EKIM YURTSEVER1, (Member, IEEE), JACOB LAMBERT 1, ALEXANDER CARBALLO 1, (Member, IEEE), AND KAZUYA TAKEDA 1, 2, (Senior Member, IEEE) 1Nagoya University, Furo-cho, Nagoya, 464-8603, Japan 2Tier4 Inc. Nagoya, Japan Corresponding author: Ekim Yurtsever (e-mail: [email protected]). ABSTRACT Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of state-of-the-art is improved further. This paper discusses unsolved problems and surveys the technical aspect of automated driving. Studies regarding present challenges, high- level system architectures, emerging methodologies and core functions including localization, mapping, perception, planning, and human machine interfaces, were thoroughly reviewed. Furthermore, many state- of-the-art algorithms were implemented and compared on our own platform in a real-world driving setting. The paper concludes with an overview of available datasets and tools for ADS development. INDEX TERMS Autonomous Vehicles, Control, Robotics, Automation, Intelligent Vehicles, Intelligent Transportation Systems I. INTRODUCTION necessary here. CCORDING to a recent technical report by the Eureka Project PROMETHEUS [11] was carried out in A National Highway Traffic Safety Administration Europe between 1987-1995, and it was one of the earliest (NHTSA), 94% of road accidents are caused by human major automated driving studies. The project led to the errors [1]. Against this backdrop, Automated Driving Sys- development of VITA II by Daimler-Benz, which succeeded tems (ADSs) are being developed with the promise of in automatically driving on highways [12].
    [Show full text]
  • Fog Computing for Detecting Vehicular Congestion, an Internet of Vehicles Based Approach: a Review
    > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 Fog Computing for Detecting Vehicular Congestion, An Internet of Vehicles based Approach: A review Arnav Thakur and Reza Malekian, Senior Member, IEEE double by the year 2020 [3]. To enhance the efficiency of the Abstract—Vehicular congestion is directly impacting the transportation sector and reduce the associated economic and efficiency of the transport sector. A wireless sensor network for environmental consequences, an accurate real-time vehicular vehicular clients is used in Internet of Vehicles based solutions traffic congestion identification system is required to be used for traffic management applications. It was found that vehicular in effective traffic management schemes that improve traffic congestion detection by using Internet of Vehicles based connected vehicles technology are practically feasible for flow and utilization of road infrastructure. congestion handling. It was found that by using Fog Computing Vehicular congestion is quantified by using the traffic based principles in the vehicular wireless sensor network, density estimate metric which is the number of vehicles per communication in the system can be improved to support larger unit area [4]. The traffic density estimation techniques use number of nodes without impacting performance. In this paper, parameters that include road occupancy rates, difference of connected vehicles technology based vehicular congestion incoming and outgoing traffic in an observation area, traffic identification techniques are studied. Computing paradigms that can be used for the vehicular network are studied to develop a flow estimation and motion detection and tracking to identify practically feasible vehicular congestion detection system that congestion [5].
    [Show full text]
  • An Intelligent Edge-Chain Enabled Access Control Mechanism For
    This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2021.3061467, IEEE Internet of Things Journal JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 1 An Intelligent Edge-Chain Enabled Access Control Mechanism for IoV Yuanni Liu, Man Xiao, Shanzhi Chen, Fellow, IEEE, Fan Bai, Jianli Pan, Member, IEEE, Di Zhang, Senior Member, IEEE Abstract—The current security method of Internet of Vehicles the amounts of vehicles exceed one billion and is expected (IoV) systems is rare, which makes it vulnerable to various to reach two billion by 2035 [6], [7]. As explosive on-road attacks. The malicious and unauthorized nodes can easily in- devices are connecting to Internet, communication security vade the IoV systems to destroy the integrity, availability, and confidentiality of information resources shared among vehicles. becomes a big issue. As we know, the communication security Indeed, access control mechanism can remedy this. However, as method of current IoV devices is rare, making it easy to be a static method, it cannot timely response to these attacks. To attacked. Such malicious attacks include replay, camouflage, solve this problem, we propose an intelligent edge-chain enabled and message tampering attacks et al. [8]. The attacked IoV access control framework with vehicle nodes and RoadSide Units devices may rise potential risks, such as critical electronic (RSUs) in this study. In our scenario, vehicle nodes act as lightweight nodes, whereas RUSs serve as full and edge nodes control unit hacking and control, untrustworthy messages from to provide access control services.
    [Show full text]
  • From Vehicular Ad-Hoc Networks to Internet of Vehicles
    From Vehicular Ad-hoc Networks to Internet of Vehicles Eugen Borcoci University Politehnica Bucharest Electronics, Telecommunications and Information Technology Faculty ( ETTI) [email protected] NexComm 2017 Conference, April 23-27, Venice Slide 1 From Vehicular Ad-hoc Networks to Internet of Vehicles Acknowledgement This overview is compiled and structured by the author, based on public documents, like conferences material, studies, research papers, standards, projects, overviews, etc. (see specific references in the text and Reference list). Given the extension of the topics, this presentation is limited to a high level overview only, being mainly focused on architectural aspects. NexComm 2017 Conference, April 23-27, Venice Slide 2 From Vehicular Ad-hoc Networks to Internet of Vehicles Motivation of this talk The traditional Intelligent Transport System (ITS) has significantly evolved, including vehicular communication Main communications: V2V, V2R, V2I Vehicular ad-hoc Networks (VANET) VANET – is an important part of the ITS VANET (special class of Mobile ad-hoc Network - MANET ) has both technical and business-related limitations still - not very large scale deployment in the world Recent approach: IoV – significant extension of the VANET capabilities global network of vehicles – enabled by Wireless Access Technologies (WAT) involving Internet and including heterogeneous access networks IoV – special case of Internet of Things (IoT) IoV Target domains: vehicles driving and safety (basic function – in VANET) and additionally: • urban traffic management, automobile production • repair and vehicle insurance, road infrastructure construction and repair, logistics and transportation, etc. NexComm 2017 Conference, April 23-27, Venice Slide 3 CONTENTS 1. Introduction 2. Vehicular networks - short overview 3. IoV objectives, use cases and challenges 4.
    [Show full text]
  • Position Prediction for Routing in Software Defined Internet of Vehicles
    Journal of Communications Vol. 15, No. 2, February 2020 Position Prediction for Routing in Software Defined Internet of Vehicles Muhammad Ali Jibran1, Muhammad Tahir Abbas2, Adeel Rafiq1, and Wang-Cheol Song1 1, Jeju National University, Jeju, South Korea 2 Karlstad University, Karlstad, Sweden Email: [email protected]; [email protected] Abstract—By the prediction of future location for a vehicle in In the past few years, vehicle to vehicle (V2V) Internet of Vehicles (IoV), data forwarding schemes can be communication gain a lot of attention because of its further improved. Major parameters for vehicle position potential to make our journey comfortable on the roads. prediction includes traffic density, motion, road conditions, and The core requirement of connected cars include a reliable vehicle current position. In this paper, therefore, our proposed and fast communication with very low latency response system enforces the accurate prediction with the help of real- time traffic from the vehicles. In addition, the proposed Neural to and from a service provider. In the meanwhile, it needs Network Model assists Edge Controller and centralized to be more efficient to manage a huge number of requests controller to compute and predict vehicle future position inside simultaneously with no traffic congestion. In ITS, a and outside of the vicinity, respectively. Last but not least, in vehicle on the road always initiates a new connection order to get real-time data, and to maintain a quality of request towards the traffic controller in case of path experience, the edge controller is explored with Software failure. Traffic controller estimates a new path each time Defined Internet of Vehicles.
    [Show full text]
  • Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
    Computers, Materials & Continua CMC, vol.65, no.1, pp.653-681, 2020 Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks Fei Li1, *, Jiayan Zhang1, Edward Szczerbicki2, Jiaqi Song 1, Ruxiang Li 1 and Renhong Diao1 Abstract: The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated the intrusion detection system based on the in-vehicle system. We combined two algorithms to realize the efficient learning of the vehicle’s boundary behavior and the detection of intrusive behavior. In order to verify the accuracy and efficiency of the proposed model, it was evaluated using real vehicle data. The experimental results show that the combination of the two technologies can effectively and accurately identify abnormal boundary behavior. The parameters of the model are self-iteratively updated using the time-based back propagation algorithm. We verified that the model proposed in this study can reach a nearly 96% accurate detection rate. Keywords: Internet of vehicles, safety protection technology, intrusion detection system, advanced auto-encoder, recurrent neural network, time-based back propagation algorithm. 1 Introduction In recent years, intelligent vehicles, a fusion of Internet technology and the machinery manufacturing industry, have resulted in the development of comprehensive information services for travel and daily commutes [Unluturk, Oguz and Atay (2015); Contreras- Castillo, Zeadally and Guerrero-Ibañez (2017)].
    [Show full text]
  • The Concepts of Connected Car and Internet of Cars and Their Impact on Future People Mobility
    INFORMATION SYSTEMS IN MANAGEMENT Information Systems in Management (2017) Vol. 6 (3) 234 −245 THE CONCEPTS OF CONNECTED CAR AND INTERNET OF CARS AND THEIR IMPACT ON FUTURE PEOPLE MOBILITY AGNIESZKA SZMELTER Department of Logistics, University of Gda ńsk (UG) Technological convergence has had a huge impact on development of automo- tive industry. Two main concepts related to mobile technology and the Internet of Things (IoT) in this industry are car connectivity and Internet of Cars (IoC). The ar- ticle aims to present these two concepts with special emphasis on the characteristics of people mobility in future cities. Keywords: automotive, logistics, information logistics, convergence, technological convergence, internet of things, internet of cars, connected car, car connectivity, mobility, public transport. 1. Introduction The global economy, which is currently characterized by development of mo- bile and Internet technologies, is in large part composed of the services sector. A new paradigm appeared: information and communication technologies enable achievement of the economic and / or social objectives by use of cooperation methods (including sharing). ICT contribute to the acceleration of economic recov- ery and the creation of "sustainable digital future" [7]. This paper aims to achieve cognitive objective, which is to present the impact of technological developments in automotive industry (especially the concepts of car connectivity and Internet of Cars) on the development of new people mobility behaviour in cities. The author hypothesizes that technological convergence, pre- sent in currently-sold cars and cars of the future significantly contributes and will contribute to development of new patterns of mobility in cities. The main research method used in the study is analysis of secondary sources, including literature and branch studies made by experts in automotive industry.
    [Show full text]
  • Huawei HCIA-Iot V. 2.5 Evaluation Questions Michel Bakni
    Huawei HCIA-IoT v. 2.5 Evaluation Questions Michel Bakni To cite this version: Michel Bakni. Huawei HCIA-IoT v. 2.5 Evaluation Questions. Engineering school. Huawei HCIA-IoT v. 2.5, Bidart, France. 2021, pp.77. hal-03189245 HAL Id: hal-03189245 https://hal.archives-ouvertes.fr/hal-03189245 Submitted on 2 Apr 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License Huawei HCIA-IoT v. 2.5 Evaluation Questions March 2021 Michel BAKNI Author: Michel BAKNI Editor: Sandra HANBO Version: 1.0 , 2021 DOI: 10.6084/m9.figshare.14336687 Copyright notice This work is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) You are free to: Share — copy and redistribute the material in any medium or format Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
    [Show full text]
  • Internet of Autonomous Vehicles: Architecture, Features, and Socio-Technological Challenges Furqan Jameel, Zheng Chang, Jun Huang, Tapani Ristaniemi
    ACCEPTED IN IEEE WIRELESS COMMUNICATIONS 1 Internet of Autonomous Vehicles: Architecture, Features, and Socio-Technological Challenges Furqan Jameel, Zheng Chang, Jun Huang, Tapani Ristaniemi Abstract Mobility is the backbone of urban life and a vital economic factor in the development of the world. Rapid urbanization and the growth of mega-cities is bringing dramatic changes in the capabilities of vehicles. Innovative solutions like autonomy, electrification, and connectivity are on the horizon. How, then, we can provide ubiquitous connectivity to the legacy and autonomous vehicles? This paper seeks to answer this question by combining recent leaps of innovation in network virtualization with remarkable feats of wireless communications. To do so, this paper proposes a novel paradigm called the Internet of autonomous vehicles (IoAV). We begin painting the picture of IoAV by discussing the salient features, and applications of IoAV which is followed by a detailed discussion on the key enabling technologies. Next, we describe the proposed layered architecture of IoAV and uncover some critical functions of each layer. This is followed by the performance evaluation of IoAV which shows significant advantage of the proposed architecture in terms of transmission time and energy consumption. Finally, to best capture the benefits of IoAV, we enumerate some social and technological challenges and explain how some unresolved issues can disrupt the widespread use of autonomous vehicles in the future. Index Terms Autonomous vehicles, Autonomy, Internet of autonomous vehicles (IoAV), Technological challenges I. INTRODUCTION The development of the automotive landscape in the coming years will be significantly influenced by the global political and economic conditions. The idea of sustainability against the background of dwindling and rapidly increasing supplies of fossil fuels will also be consolidated on a global scale [1].
    [Show full text]
  • An Intrusion Detection System in Connected Vehicles
    electronics Article Cybersecurity in Automotive: An Intrusion Detection System in Connected Vehicles Francesco Pascale 1,* , Ennio Andrea Adinolfi 2 , Simone Coppola 2 and Emanuele Santonicola 2 1 Department of Energy, Polytechnic of Milan, 20156 Milan, Italy 2 Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy; eadinolfi@unisa.it (E.A.A.); [email protected] (S.C.); [email protected] (E.S.) * Correspondence: [email protected] Abstract: Today’s modern vehicles are connected to a network and are considered smart objects of IoT, thanks to the capability to send and receive data from the network. One of the greatest challenges in the automotive sector is to make the vehicle secure and reliable. In fact, there are more connected instruments on a vehicle, such as the infotainment system and/or data interchange systems. Indeed, with the advent of new paradigms, such as Smart City and Smart Road, the vision of Internet of Things has evolved substantially. Today, we talk about the V2X systems in which the vehicle is strongly connected with the rest of the world. In this scenario, the main aim of all connected vehicles vendors is to provide a secure system to guarantee the safety of the drive and persons against a possible cyber-attack. So, in this paper, an embedded Intrusion Detection System (IDS) for the automotive sector is introduced. It works by adopting a two-step algorithm that provides detection of a possible cyber-attack. In the first step, the methodology provides a filter of all the messages on the Controller Area Network (CAN-Bus) thanks to the use of a spatial and temporal Citation: Pascale, F.; Adinolfi, E.A.; analysis; if a set of messages are possibly malicious, these are analyzed by a Bayesian network, which Coppola, S.; Santonicola, E.
    [Show full text]
  • Autonomous Vehicle Technology: a Guide for Policymakers
    Autonomous Vehicle Technology A Guide for Policymakers James M. Anderson, Nidhi Kalra, Karlyn D. Stanley, Paul Sorensen, Constantine Samaras, Oluwatobi A. Oluwatola C O R P O R A T I O N For more information on this publication, visit www.rand.org/t/rr443-2 This revised edition incorporates minor editorial changes. Library of Congress Cataloging-in-Publication Data is available for this publication. ISBN: 978-0-8330-8398-2 Published by the RAND Corporation, Santa Monica, Calif. © Copyright 2016 RAND Corporation R® is a registered trademark. Cover image: Advertisement from 1957 for “America’s Independent Electric Light and Power Companies” (art by H. Miller). Text with original: “ELECTRICITY MAY BE THE DRIVER. One day your car may speed along an electric super-highway, its speed and steering automatically controlled by electronic devices embedded in the road. Highways will be made safe—by electricity! No traffic jams…no collisions…no driver fatigue.” Limited Print and Electronic Distribution Rights This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited. Permission is given to duplicate this document for personal use only, as long as it is unaltered and complete. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial use. For information on reprint and linking permissions, please visit www.rand.org/pubs/permissions.html. The RAND Corporation is a research organization that develops solutions to public policy challenges to help make communities throughout the world safer and more secure, healthier and more prosperous.
    [Show full text]